Kaufman Adaptive Moving Average for Noise-Adjusted Trend Following

Summary

This document explains a trend-following approach based on Kaufman’s Adaptive Moving Average (KAMA). The indicator adjusts its smoothing in relation to directional price change versus accumulated price movement: it responds more slowly when movement is noisy and more quickly when directional movement strengthens. The strategy compares price with KAMA to determine whether to hold a long or short position, with an option to reverse the direction of its signals.

The document provides the indicator formula, configurable lookback, and published test settings for a Bitcoin futures market, but it gives no performance statistics or evidence that the approach is profitable. It notes that KAMA can still whipsaw in sideways markets, may lag reversals, and does not account for fees or slippage. Suggested extensions include tuning the lookback, adding stop losses and signal filters, and allowing re-entry. The described simplicity comes with limited trade management detail, so risk controls and execution assumptions would need separate evaluation.

Key ideas

• KAMA changes its responsiveness according to directional movement relative to recent price noise.
• The strategy uses price relative to KAMA to select long or short exposure, with an optional reversal setting.
• A configurable lookback controls the efficiency ratio used in the indicator calculation.
• Sideways markets can create misleading signals, while smoothing can delay responses to reversals.
• The published settings do not include performance results, and transaction costs are not modeled in the explanation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.